from keras.models import Model
from keras.layers import Input, Conv3D, MaxPooling3D, UpSampling3D
# ! <<< Outdated.
# from keras.layers.normalization import BatchNormalization
from keras.layers.normalization.batch_normalization_v1 import BatchNormalization
# ! >>>
from keras.layers.core import SpatialDropout3D, Activation
from keras import backend as K
from keras.layers.merge import concatenate
import math
import numpy as np

def dice_coef(y_true, y_pred):
    y_true_f = K.flatten(y_true)
    y_pred_f = K.flatten(y_pred)
    intersection = K.sum(y_true_f * y_pred_f)
    return (2.0 * intersection + K.epsilon()) / (K.sum(y_true_f) + K.sum(y_pred_f) + K.epsilon())

def dice_coef_loss(y_true, y_pred):
    return -dice_coef(y_true, y_pred)